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DWE: Decrypting Learning with Errors with Errors.

Authors :
Song Bian
Masayuki Hiromoto
Takashi Sato
Source :
DAC: Annual ACM/IEEE Design Automation Conference; 2018, Issue 55, p361-366, 6p
Publication Year :
2018

Abstract

The Learning with Errors (LWE) problem is a novel foundation of a variety of cryptographic applications, including quantumly-secure public-key encryption, digital signature, and fully homomorphic encryption. In this work, we propose an approximate decryption technique for LWE-based cryptosystems. Based on the fact that the decryption process for such systems is inherently approximate, we apply hardware-based approximate computing techniques. Rigorous experiments have shown that the proposed technique simultaneously achieved 1.3x (resp., 2.5x) speed increase, 2.06x (resp., 7.89x) area reduction, 20.5% (resp., 4x) of power reduction, and an average of 27.1% (resp., 65.6%) ciphertext size reduction for public- key encryption scheme (resp., a state-of-the-art fully homomorphic encryption scheme). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0738100X
Issue :
55
Database :
Complementary Index
Journal :
DAC: Annual ACM/IEEE Design Automation Conference
Publication Type :
Conference
Accession number :
155539275
Full Text :
https://doi.org/10.1145/3195970.3196032